Trial reportJournal of cardiovascular computed tomography
Computed tomography-based high-risk coronary plaque score to predict acute coronary syndrome among patients with acute chest pain--Results from the ROMICAT II trial.
Trial report in Journal of cardiovascular computed tomography. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06956924 (CT-Based Abdominal Aortic Calcium Score and CAD-RADS 2.0 in Elderly Chest Pain), which is not on this map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
CT-Based Abdominal Aortic Calcium Score and CAD-RADS 2.0 in Elderly Chest Pain: A Cohort Study
Who cites it
36 citing papers in PubMed.
- Quantitative coronary plaque analysis predicts high-risk plaque morphology on coronary computed tomography angiography: results from the ROMICAT II trial.The international journal of cardiovascular imaging · 2018Trial
- Association of Low-Attenuation Noncalcified Plaque Shape and Degree of Intraplaque Embeddedness Using Atherosclerotic Imaging-enabled Quantitative CT with Acute Coronary Syndrome.Radiology. Cardiothoracic imaging · 2026Article
- Is Imaging of a Single Vessel Sufficient to Assess Pan-Coronary Vulnerability?Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions · 2026Article
- Innovations In Artificial Intelligence-Guided Atherosclerosis Cardiovascular Imaging: From Detection to Prognosis.Current atherosclerosis reports · 2026Review
- Coronary atherosclerosis on AI-based plaque analysis in patients with chest pain and calcium score zero.The international journal of cardiovascular imaging · 2026Article
- Data-driven atherosclerotic plaque profiles from QAngio-CT associated with functional impairments assessed with PET-CT.Archivos de cardiologia de Mexico · 2026Article
- PlaqueViT: a vision transformer model for fully automatic vessel and plaque segmentation in coronary computed tomography angiography.European radiology · 2025Article
- Prevalence and characteristics of coronary artery disease in master athletes with ST-segment depression or high-risk premature ventricular beats at pre-participation exercise testing.European heart journal open · 2025Article
- The Role of Cardiac Computed Tomography Angiography in Risk Stratification for Coronary Artery Disease.Journal of the Society for Cardiovascular Angiography & Interventions · 2024Review
- Coronary Artery Stenosis and High-Risk Plaque Assessed With an Unsupervised Fully Automated Deep Learning Technique.JACC. Advances · 2024Article
- Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.Nature reviews. Cardiology · 2024Review
- A novel deep learning model for a computed tomography diagnosis of coronary plaque erosion.Scientific reports · 2023Article
- Impact of virtual monoenergetic levels on coronary plaque volume components using photon-counting computed tomography.European radiology · 2023Article
- Cardiac Computed Tomography Angiography in CAD Risk Stratification and Revascularization Planning.Diagnostics (Basel, Switzerland) · 2023Review
- Coronary allograft vasculopathy in post-heart transplant patients: pathogenesis and role of cardiac computed tomography in diagnosis-a comprehensive review.Annals of medicine and surgery (2012) · 2023Article
- High-quality annotations for deep learning enabled plaque analysis in SCAPIS cardiac computed tomography angiography.Heliyon · 2023Article
- Does Coronary Plaque Morphology Matter Beyond Plaque Burden?Current atherosclerosis reports · 2023Review
- Management of Acute Coronary Syndrome in the Older Adult Population: A Scientific Statement From the American Heart Association.Circulation · 2023Review
- [Computed tomography and magnetic resonance imaging in cardiac diagnostics-how to choose the right modality : A guide based on the new guidelines of the European Society of Cardiology (ESC)].Radiologie (Heidelberg, Germany) · 2022Review
- Plaque Burden and 1-Year Outcomes in Acute Chest Pain: Results From the Multicenter RAPID-CTCA Trial.JACC. Cardiovascular imaging · 2022Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundCoronary computed tomography angiography (CTA) can be used to detect and quantitatively assess high-risk plaque features.
objectiveTo validate the ROMICAT score, which was derived using semi-automated quantitative measurements of high-risk plaque features, for the prediction of ACS. MATERIAL AND
methodsWe performed quantitative plaque analysis in 260 patients who presented to the emergency department with suspected ACS in the ROMICAT II trial. The readers used a semi-automated software (QAngio, Medis medical imaging systems BV) to measure high-risk plaque features (volume of <60HU plaque, remodeling index, spotty calcium, plaque length) and diameter stenosis in all plaques. We calculated a ROMICAT score, which was derived from the ROMICAT I study and applied to the ROMICAT II trial. The primary outcome of the study was diagnosis of an ACS during the index hospitalization.
resultsPatient characteristics (age 57 ± 8 vs. 56 ± 8 years, cardiovascular risk factors) were not different between those with and without ACS (prevalence of ACS 7.8%). There were more men in the ACS group (84% vs. 59%, p = 0.005). When applying the ROMICAT score derived from the ROMICAT I trial to the patient population of the ROMICAT II trial, the ROMICAT score (OR 2.9, 95% CI 1.4-6.0, p = 0.003) was a predictor of ACS after adjusting for gender and ≥ 50% stenosis. The AUC of the model containing ROMICAT score, gender, and ≥ 50% stenosis was 0.91 (95% CI 0.86-0.96) and was better than with a model that included only gender and ≥ 50% stenosis (AUC 0.85, 95%CI 0.77-0.92; p = 0.002).
conclusionsThe ROMICAT score derived from semi-automated quantitative measurements of high-risk plaque features was an independent predictor of ACS during the index hospitalization and was incremental to gender and presence of ≥ 50% stenosis.
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Registered trials
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